Available Positions

Skoltech is pleased to announce a number of Ph.D. positions are available on a rolling bases in the following research programs and labs. Applications may be submitted at http://apply.skoltech.ru/phd and questions directed to

*protected email*. For more details, please see below:

Center for Energy Systems

Assistant Professor Aldo Bischi invites applications for two PhD positions in the Skoltech Center for Energy Systems, one in the area of smart-grid optimal scheduling and design, and another in the area of district heating optimal scheduling and design. Energy systems are evolving toward distributed power generation integrating both electric and thermal power together with high penetration of renewable sources, active demand, and energy storage systems. In this way, it will be possible to achieve both primary energy and CO2 emissions reduction and economic savings due to a smart coupling of several generation units that will accommodate fluctuating loads with variable commodity prices. This is true for remote villages and microgrids, as well as for grid connected applications both at small and large scale, e.g. industry and district heating networks. The candidates are expected to have an energy/thermodynamic background together with a strong mathematical and information technology background. Experimental experience is also welcome for lab activities. The projects will be undertaken in collaboration with our Russian and international partners and the industry and may incorporate visits to our international partners like MIT and Caltech.

Computational Electromagnetics

The Computational Prototyping Group led by Professor Athanasios Polimeridis invites applications for PhD positions in computational mathematics with focus on some subset of the following areas: computational wave propagation, optimization and inverse problems, integral equations, fast algorithms, RF interactions with biological tissues, quantum/thermal fluctuating phenomena. Candidates are expected to have a good background in computational mathematics and should be comfortable with one or more of the areas mentioned above. Expertise in parallel programming and open-source software development is a big plus. The balance of work between theoretical and computational will depend on the candidate’s affinities.

Center for Data Science

The Skoltech Center for Data Science seeks outstanding candidates in the area of data management and data science. Prospective areas of research include topics on the manipulation, indexing, analysis, privacy, and security of graph, spatio-temporal, streaming, semantic web, and time-series data. Applications should have a strong background in computer science, including data structures, algorithms, and machine learning, excellent programming skills, teamwork capacity, and ability to meet deadlines. The group is led by professor Panagiotis Karras.

Multiscale Computational Methods

Ph.D. positions are available in the Multiscale and Multiphysics Computational Methods group led by professor Alexander Shapeev. The research focus will be in multiscale and multiphysics computational methods and numerical analysis. The primary applications are related to materials science and include large atomistic and quantum mechanics simulations. See this page for some details on the methods and applications. Other applications may include computing behavior of composites, photonic crystals, or materials for energy storage. Successful candidates will have a master degree or equivalent in computational science, applied mathematics, or related field. Motivated candidates with a degree in physics, materials science, or related field will also be considered. Additional details can be found here.

Computer vision and image processing

Professor Stamatios Lefkimmiatis invites applications for PhD positions in the areas of computer vision and image processing. The research focus will be on mathematical image modeling, computational methods for inverse imaging problems, large-scale optimization, and fast numerical methods. Successful candidates are expected to have a masters degree in electrical engineering, computer science, or applied mathematics. Previous experience in image/signal processing and/or machine learning is highly desirable. Applicants should have a strong theoretical background and a desire to use mathematical

tools in their research. A good knowledge of C/C++, Python, Matlab and/or Cuda is also required.

Multiscale Materials Modeling

The PhD track in the group is focused on multiscale modeling of materials starting from atomistic scale to device scale. Applicants will acquire strong skills in computational and theoretical materials science. Various background levels are accepted. Required are basic knowledge of physics and chemistry of materials, quantum mechanics and statistical physics, computational skills. Two kinds of research projects are available: 1) modeling of materials and devices for applications (cathode/anode materials for Li-ion batteries, conjugated polymers for field-effect transistors, organic solar cells) and 2) development of new methods for materials modeling (energy and charge transport in molecular systems and polymers, ionic transport in solids and liquids, high throughput screening and computational design of materials). The group is led by professor Andriy Zhugayevych.

Laboratory of Nanomaterials

We currently have one position available in the area of transparent and conductive single-walled carbon nanotube (CNT) films. This project is devoted to tailoring the electronic signature of CNT films by chemical dopants. These highly transparent and conductive films will be tested in efficient heterojunction solar cells and supercapacitors. Applicants should hold an MSc or equivalent in chemistry or materials science, or related fields, and will work under the direction of professor Albert Nasibulin.

Theory of Complex Quantum Systems

The Theory of Complex Quantum Systems research group seeks Ph.D. candidates with interests in superconducting materials or relaxation and chaos in many-particle systems. Applicants should have a master’s degree or equivalent in physics with good training in quantum mechanics. The group is led by professor Boris Fine.

Nanoelectronics and Nanophotonics Group

The research program in the Nanoelectronics and Nanophotonics Group at Skoltech focuses on the theory and modeling of novel materials for photonics applications in close collaboration with experimental groups and industrial partners. Successful applicants should have deep mathematical knowledge; experience with numerical solutions is desired. The group is led by professor Vasili Perebeinos.

The new Skoltech Space Center seeks outstanding candidates for several positions in space science and technology. Priority research areas include: data exploitation, space environment and space physics, instruments and data, systems architecture and engineering, navigation and geodesy, and human spaceflight. Ph.D. students will be heavily involved in the activities of the new Center in Moscow, as well as be provided with opportunities to take additional courses or research at MIT, EPFL, UCLA, and TU-Berlin.

Skoltech Center for Energy Systems

The Skoltech Center for Energy Systems is focused on smart grids, energy infrastructure (electric power, gas, heat), energy markets and regulation, and power electronics and devices. The Center aims to address these challenges via an interdisciplinary approach, combining the efforts of engineers, physicists, mathematicians, statisticians, economists, and other social scientists. Ph.D. students in this center will closely collaborate with scholars and research groups at MIT, Caltech, and other research universities. For inquiries, please contact Professor Janusz Bialek or Professor Alexander Ustinov.

Laboratory of Computational and Structural Transcriptomics

Professor Dmitry Pervouchine invites applications for a PhD position in the Skoltech laboratory of Computational and Structural Transcriptomics. The project is dedicated to studying RNA production pathways, particularly in the context of RNA-chromatin interactions and epigenetic signals, by using integrative next generation sequencing (NGS). The goal is to build a comprehensive model of transcription and post-transcriptional processing from recent high resolution NGS data using artificial intelligence and advanced statistical models.

Minimum qualifications of the candidates expected to join this group are:

· a degree in biology, mathematics, statistics, computer science, physics, chemistry, bioinformatics, or a related field with knowledge of statistics;

· strong computational background with proficiency in at least one programming language, preferably with experience in LINUX;

· spoken and written English proficiency and excellent communication skills.

Applicants with research experience in software pipelines for large-scale data analysis, applications of machine learning, and the analysis of gene networks in disease are particularly encouraged to apply.